In this paper we propose a new approach to estimate the ratio of two probability density functions. The proposed approach is inspired by the kernel based function approximation technique. We apply this estimator to derive an estimator of mutual information and show that this estimator can be successfully used to detect dependence between two random variables.
|Title of host publication||Machine Learning for Signal Processing, 2009. MLSP 2009. IEEE International Workshop on|
|Publisher||Institute of Electrical and Electronics Engineers (IEEE)|
|Number of pages||6|
|Publication status||Published - 2009|